November 9, 2025Open Access

A Proprietary Model-Based Safety Response Framework for AI Agents

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Authors

LQLi QiNingbo University of Technology JXJianjun XuNortheast Petroleum University PWPeng WeiUniversity of Regina

Discussion

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Implication

This framework improves result traceability and addresses security issues in large language models, suggesting enhanced reliability for critical applications.

Key Points

Framework achieves significant security enhancements for AI agents, addressing critical deployment concerns.
First-level evaluation shows strong result traceability, confirming meaningful reliability against security issues.
Observational analysis of the framework demonstrates remarkable risk recall rate of 99.3%, ensuring adaptive handling.
Implications indicate potential for building high-security AI systems, but practical applications remain to be explored.

Cite This Study

Qi et al. (2025) studied this question.

synapsesocial.com/papers/690fdcdaf60c54d04ea380c2 https://doi.org/10.48550/arxiv.2511.03138

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November 9, 2025Open Access

A Proprietary Model-Based Safety Response Framework for AI Agents

View Full Paper

Ask AI

Bookmark

Authors

LQLi QiNingbo University of Technology JXJianjun XuNortheast Petroleum University PWPeng WeiUniversity of Regina

Discussion

Member takes

Implication

This framework improves result traceability and addresses security issues in large language models, suggesting enhanced reliability for critical applications.

Key Points

Framework achieves significant security enhancements for AI agents, addressing critical deployment concerns.
First-level evaluation shows strong result traceability, confirming meaningful reliability against security issues.
Observational analysis of the framework demonstrates remarkable risk recall rate of 99.3%, ensuring adaptive handling.
Implications indicate potential for building high-security AI systems, but practical applications remain to be explored.

Cite This Study

Qi et al. (2025) studied this question.

synapsesocial.com/papers/690fdcdaf60c54d04ea380c2 https://doi.org/10.48550/arxiv.2511.03138

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